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Active Detecting DDoS Attack Approach Based on Entropy Measurement for the Next Generation Instant Messaging App on Smartphones

Hsing‐Chung Chen1,2, Shyi‐Shiun Kuo1,3

1 Department of Computer Science and Information Engineering, Asia University, No. 500, Lioufeng Rd., Wufeng Dist., Taichung City, Taiwan
2 Dept. of Medical Research, China Medical University Hospital, China Medical University, Taichung City, Taiwan
3 Dept. of Multimedia Animation and Application, Nan Kai University of Technology, No. 568, Zhongzheng Rd., Caotun Township, Nantou County, Taiwan

* Corresponding Authors: Hsing‐Chung Chen, ,

Intelligent Automation & Soft Computing 2019, 25(1), 217-228. https://doi.org/10.31209/2018.100000057

Abstract

Nowadays, more and more smartphones communicate to each other’s by using some popular Next Generation Instant Messaging (NGIM) applications (Apps) which are based on the blockchain (BC) technologies, such as XChat, via IPv4/IPv6 dual stack network environments. Owing to XChat addresses are soon to be implemented as stealth addresses, any DoS attack activated form malicious XChat node will be treated as a kind of DDoS attack. Therefore, the huge NGIM usages with stealth addresses in IPv4/IPv6 dual stack mobile networks, mobile devices will suffer the Distributed Denial of Service (DDoS) attack from Internet. The probing method is deployed in this paper by using the active ICMP (Internet Control Message Protocol) protocol. Thus, the aim of this paper is to provide the active approach based on the integrated entropy calculations for the NGIM traffics, the numbers of IPv4 and IPv6 addresses of the abnormal events found and counted after active inquiring ICMP procedure. However, many DDoS attacks in Internet were found to paralyze NGIM Apps on smartphones. It is a lightweight approach could be applied in mobile device.

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Cite This Article

H. Chen and . S. Kuo, "Active detecting ddos attack approach based on entropy measurement for the next generation instant messaging app on smartphones," Intelligent Automation & Soft Computing, vol. 25, no.1, pp. 217–228, 2019.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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